Motion planning and control for a robot performer

The authors describe robot motion planning in a dynamic environment, that is, a trajectory generation to attain a working purpose with redundancy free to use under the restriction of time and space. Emphasis is placed on juggling. A parametric representation of the robot motion makes it easy to generate an appropriate trajectory of the end-effector for juggling tasks. A hierarchical learning control strategy is effective to generate a desired motion pattern for juggling which is not given beforehand. To juggle several balls repeatedly by a real robot the location and time at which a ball is caught by using sensory feedback signals is predicted, and the end-tip trajectory is modified. Experimental results obtained using a 2-degree-of-freedom direct-drive manipulator are shown